Multiomic studies to improve fruit quality of berry fruits

In this study we are going to use different omic-techniques to analyze fruits of three species of berries such as strawberry, raspberry and black currant. Berry fruit are well appreciated for their delicate flavor and nutraceutical properties, with consumer demand increasing over the last years. Furthermore, climate change and market globalization have made necessary to improve the production while maintaining fruit quality traits. Goodberry project is developping analytical platforms, covering from transcriptomic to metabolites and volatile compounds analysis, to find new factors controlling plant adaptation, fruit production and quality. In this study we implement the metabolomic analysis of strawberry, raspberry and black currant fruits from the 2017 harvest, as well as 2018 harvest during this year. To analyze and compare the data we use multiomic tools and bioinformatics to extract properly conclusion The analyses take different berry cultivars, adapted to diverse environments, were grown in 2017 and 2018 in different latitudes (Germany, France, Norway, Italy, Poland and Scotland). The data comes from a combination of gas-chromatography-mass spectrometry (GC-TOF-MS) and headspace solid phase micro extraction (HS-SPME) coupled with GC-MS was used to semi-quantify fruit primary metabolome and volatilome. Around 50 key primary metabolites, including sugars and acids, which are fundamental factors influencing fruit taste and 75 volatiles, responsible of the aroma, were identified across the different genotypes and climates. Multivariate statistical approaches allow us to point out the genetic and environmental factors underlying complex metabolic traits involved in fruit quality. Preliminary analysis showed that both climate and genetic factors influence primary metabolite and volatile content, even if the environment seems to have a stronger impact on the first one.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Application of multiomic technologies to study the environmental impact on berry fruit quality

Berries, such as strawberry, raspberry and black currant, are well appreciated for their delicate flavor and nutraceutical properties, with consumer demand increasing over the last years. However, climate change and market globalization have made necessary to improve the production while maintaining fruit quality traits. Among the EU GoodBerry project’s objetive are develop state-of-the-art analytical platforms, covering from transcriptomic to metabolites and volatile compounds analysis, to find new factors controlling plant adaptation, fruit production and quality and use the data to face climate changes. Here we present the metabolomic analysis of strawberry, raspberry and black currant fruits from the 2017 harvest. Different berry cultivars, adapted to diverse environments, were grown in 2017 and 2018 in different latitudes (Germany, France, Norway, Italy and Poland) combination of spectrometry techniques was used to semi-quantify fruit primary metabolome and volatilome. Around 50 key primary metabolites, including sugars and acids, which are fundamental factors influencing fruit taste and 75 volatiles, responsible of the aroma, were identified across the different genotypes and climates. Multivariate statistical approaches allow us to point out the genetic and environmental factors underlying complex metabolic traits involved in fruit quality.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Impact of global warming on beef cattle production cost in Brazil

Global warming is affecting agribusiness in its economic aspects. Therefore, the prediction of the evolution of Brazilian beef cattle production cost was made using the IPCC forecast scenario for global warming. The methodology consisted of two steps: (i) the development of a fuzzy model that estimated the grazing land capacity (RP) decrease risk as a function of the changes in the average total rain index, air temperature and increase in extension of the dry season; and (ii) the design of an algorithm for predicting the decrease in production as function of the RPfuzzy model, that results in the impact in beef cattle productivity, and consequent increase in production costs. Historical environmental data from important producing counties in the Cerrado were organized and a set of fuzzy Gaussian functions were developed, and three possible settings (optimistic, medium and pessimistic) were considered. The decrease in beef cattle productivity was estimated using the losses in production due to the increase in air temperature and vulnerability of pasture capacity. The boundary settings for the total increase of production cost scenario used the number of animals per area of grazing land, the adoption of grain supplement and its future scenario; and the result output function pointed to a threshold within a variation from an increase in production cost of 80% (optimistic) to 160% (pessimistic). Under the optimistic scenario the total cost of Brazilian beef cattle production in the Cerrado became near to US$2.88 kg-1, while in the pessimistic scenario this cost reached US$ 4.16 kg-1, challenging the international competitiveness of this economic segment.O aquecimento global afeta o agronegócio em seus aspectos econômicos. Foi feita previsão daevolução do custo de produção de carne bovina brasileira usando a predição de aquecimento global do IPCC. A metodologia consistiu de duas etapas: (i) o desenvolvimento de modelo fuzzy que estimou o risco de decréscimo da capacidade de pastagens (RP) em função das mudanças no índice pluviométrico total, na temperatura do ar e na extensão da estação de seca; e (ii) o desenvolvimento de um algoritmo para predição do decréscimo da produção em função de um modelo fuzzy de RP que resulte no impacto na produtividade bovina de corte e conseqüente aumento no custo de produção. Foram organizados os dados históricos de fatores ambientais dos municípios importante produção no Cerrado e um conjunto de funções Gaussianas fuzzy foi desenvolvido e três estimativas possíveis (otimista, média e negativa) foram consideradas. O decréscimo na produtividade do gado foi estimado usando as perdas de produção devido ao acréscimo da temperatura bem como da vulnerabilidade da capacidade de pastagem. O estabelecimento dos limites para o cenário do acréscimo do custo de produção usou o número de unidade animal por área de pastagem, a adoção de suplemento de grãos e o cenário de produção futura; e o resultado da função de saída apontou para uma variação do acréscimo do custo de produção de 80% (otimista) até 160% (pessimista). Sob o cenário otimista, o custo total da produção brasileira de carne bovina no Cerrado chega a US$2,88 kg-1, enquanto no cenário pessimista este custo pode atingir US$ 4,16 kg-1, o que pode comprometer a competitividade internacional do setor